Effective methodology to mitigate multiple scattering effects in multi frequency space borne radar retrievals previous studies have shown that multiple scattering MS is a phenomenon that can…

This federal contract award to Morgan State University, a historically Black university, is for the development of an effective methodology to mitigate the impact of multiple scattering effects in multi-frequency spaceborne radar retrievals. The $317,838.71 grant is funded by the National Aeronautics and Space Administration (NASA) and will support the incorporation of an efficient 1D Monte Carlo multiple scattering model into a variational retrieval framework to address this challenge. The research aims to extend the model to simulate spaceborne radar Doppler observations and evaluate the framework using multi-frequency airborne radar data. This work is highly relevant to current NASA missions like the Global Precipitation Measurement (GPM) and future missions such as the Atmospheric Cloud Ecosystems (ACE) project. The contract does not have a set-aside designation.

Effective methodology to mitigate multiple scattering effects in multi frequency space borne radar retrievals previous studies have shown that multiple scattering MS is a phenomenon that can significantly enhance the reflectivities observed by space borne radars operating at kaband and higher. For such systems, the amount of energy emitted by the radar and reaching the receiver after multiple interactions with the precipitating atmosphere is significant and needs to be rigorously quantified and accounted for in retrievals. The recently launched global precipitation mission GPM already produced sufficient evidence that multiple scattering effects can significantly impact dual frequency space borne radar retrievals and significant multiple scattering effects are expected to be present in the observations of future missions such as the NASA atmospheric cloud ecosystems ACE. We propose the development of a multi frequency space borne radar retrieval framework that effectively mitigates the negative impact of multiple scattering through the incorporation of an efficient 1D monte carlo multiple scattering 1D MS model into a variational retrieval framework. The uncertainties in the 1D MS model will be quantified through comparisons with a more general 3D model developed within a previously funded remote sensing theory project and will be accounted for in the variational retrieval framework. The 1D MS will also be extended to simulate space borne radar doppler observations. The gradients required in the retrieval framework will be evaluated using a perturbation methodology developed in the previously funded remote sensing theory project and extended in proposed work. The entire framework will be evaluated using multi frequency airborne radar data from field campaigns. The framework is expected to be highly relevant to both current NASA missions such as GPM and future missions such as ACE. Succinctly, the primary objectives of our proposed research are to develop a multi frequency space borne radar retrieval framework insensitive to the negative impact of multiple scattering by: 1. Incorporating an efficient 1D monte carlo multiple scattering model and associated gradient evaluation methodology into a multiple frequency radar optimal estimation framework and appropriately accounting for its uncertainties by rigorously investigating its systematic and random errors; 2. Extending the 1D model and its gradient evaluation methodology to efficiently account for multiple scattering effects in doppler observations; 3. Evaluating the retrieval framework using multi frequency airborne radar observations and ground validation data from field campaigns.